2010 IEEE / WIC / ACM International Conferences

Professor of Computer Science at the University of Waikato in New Zealand where he directs the New Zealand Digital Library research project. His research interests include language learning, information retrieval, and machine learning.

Speech Title: Wikipedia and how to use it for semantic document representation

Abstract: Wikipedia is a goldmine of information; not just for its many readers, but also for the growing community of researchers who recognize it as
a resource of exceptional scale and utility. It represents a vast investment of manual effort and judgment: a huge, constantly evolving tapestry of concepts and relations that is being applied to a host of tasks.

This talk focuses on the process of "wikification"; that is, automatically and judiciously augmenting a plain-text document with pertinent hyperlinks to Wikipedia articles as though the document were itself a Wikipedia article. I first describe how Wikipedia can be used to determine semantic relatedness between concepts. Then I explain how to wikify documents by exploiting Wikipedia's internal hyperlinks for relational information and their anchor texts as lexical information. Data mining techniques are used throughout to optimize the models involved.

I will discuss applications to knowledge-based information retrieval, topic indexing, document tagging, and document clustering. Some of these perform at human levels. For example, on CiteULike data, automatically extracted tags are competitive with tag sets assigned by the best human taggers, according to a measure of consistency with other human taggers. All this work uses English, but involves no syntactic parsing, so the techniques are language independent.

Professor of Computer Science and Industrial and Systems Engineering at the University of Southern California(USC). He received his
Ph.D. from the School of Computer Science at Carnegie Mellon University. He leads the TEAMCORE Research Group at USC, with research is focused on
agent-based and multi-agent systems. He is a fellow of AAAI (Association for Advancement of Artificial Intelligence) and recipient of the ACM (Association
for Computing Machinery) SIGART Agents Research award. He is also the recipient of a special commendation given by the Los Angeles World Airports police from
the city of Los Angeles, USC Viterbi School of Engineering use-inspired research award, Okawa foundation faculty research award, the RoboCup scientific
challenge award, and the ACM recognition of service award. Prof. Tambe and his research group's papers have been selected as best papers
or finalists for best papers at more than a dozen premier Artificial Intelligence and Operations Research Conferences and workshops, and their
algorithms have been deployed for real-world use by several agencies including the LAX police, the Federal Air Marshals service and the Transportation
security administration.

Abstract: Security at major locations of economic or political importance or
transportation or other infrastructure is a key concern around the world,
particularly given the threat of terrorism. Limited security resources prevent
full security coverage at all times; instead, these limited resources must be
deployed intelligently taking into account differences in priorities of
targets requiring security coverage, the responses of the adversaries to the
security posture and potential uncertainty over the types of adversaries
faced.

Game theory is well-suited to adversarial reasoning for security resource
allocation and scheduling problems because it suggests randomized policies that
mitigate a key vulnerability of human plans: predictability. Casting the
problem as a Bayesian Stackelberg game, we have developed new algorithms for
efficiently solving such games to provide randomized patrolling or inspection
strategies; our algorithms are now deployed in multiple applications. ARMOR
(Assistant for Randomized Monitoring over Routes), our first game theoretic
application, has been deployed at the Los Angeles International Airport (LAX)
since August 2007 to randomizes checkpoints on the roadways entering the
airport and canine patrol routes within the airport terminals. IRIS, our second
application, is a game-theoretic scheduler for randomized deployment of the
Federal Air Marshals (FAMS) requiring significant scale-up in underlying
algorithms; IRIS was put into use to generate schedules in late 2009 with first
schedules created by IRIS flown by air marshals starting January 2010. Finally,
GUARDS has been deployed by the TSA (Transportation Security Administration) at
the Pittsburgh and LAX airports starting October 2009 for pilot evaluation with
a goal of potential larger-scale deployments. These applications are leading to
real-world use-inspired research. This talk will outline our algorithms, key
research results and lessons learned from these applications.

Since 1997 Alan Smeaton has been a Professor of Computing at Dublin City University where he is Deputy Director of CLARITY: Centre for Sensor Web
Technologies. His research interests are in the management of all kinds of heterogeneous, noisy, and errorsome data. Initially his research focused on
searching through text archives and then moved to image search and on to video analysis, indexing and retrieval. Since 2001 Alan has been a founder and
coordinator of TRECVid, an annual benchmarking activity with worldwide participation of approximately 400 researchers which measures the effectiveness
of content-based operations on video archives. More recently Alan has focused his work on managing information from heterogeneous sensor networks, making
sense of the flood of data that comes from sensor applications in fields as diverse as energy monitoring, sports participation, injury rehabilitation,
digital lifelogging, and environmental monitoring.

Abstract: Classical information retrieval is based around a user having an information
need, formulated as a query, and a system which matches the query against
'documents', retrieving those most likely to be relevant. In some applications
there are challenges because the 'documents' are not discrete objects but
highly inter-connected, and IR research has for decades developed models of the
processes, devised novel ranking algorithms, and developed very elaborate
benchmarking techniques for performance. But what if the information we need
or seek is not neatly divided into documents, either discrete or
inter-connected, but needs to be taken from a constant stream of data values,
namely data from sensors. These sensors cover the physical sensors around us
(environment, place, physical activities like traffic, weather, people
movement, crowd gatherings like concerts and sports events) as well as the
online sensors we have access to (blogs, tweets, etc.). Often termed the
*sensor web*, this information source is characterised as being noisy,
errorsome, unpredictable and dynamic, exactly like the real and the virtual
worlds in which we live, work and play. In this presentation I introduce
several diverse sensor web applications to show the breadth and pervasive
nature of the sensor web and I then show some of the techniques which we use to
manage the information which forms part of the sensor web.

Professor at the Universit¨¤ Degli Studi di Milano Bicocca, Milano, Italy, where she leads the Information Retrieval research Lab. Her research activity mainly concerns the modelling and design of flexible and personalized systems for the management and access to information. She is actually working on XML retrieval, Personalized Information Retrieval, Information Filtering, Document Clustering, Preference Modelling. She has co-edited seven books e several special issues of International Journals. She has published more than 170 papers on International Journals and Books, and on the Proceeding of International Conferences. She is a member of the Editorial Board of several international journals among which Fuzzy Sets and Systems (Elsevier), Web Intelligence and Agent Systems (IOS Press), and the Journal of Computational Intelligence Systems (IJCIS), Atlantis Press.

Speech Title: Issues on preference-modelling and personalization in Information Retrieval

Abstract:
In recent years there has been a great deal of research about personalization in information access. The main issue is to improve the quality of search by producing user-tailored results related to specific user needs.

In this context two key research problems concerns how to model user preferences, and how to exploit them in effective personalisation processes. This talk will address the above problems, and will discuss some important issues related to their possible solutions. The talk will also point out some research directions worth to be explored.

Biography: Distingushed Professor of the College of Science and Engineering
at the University of Minnesota.
She specializes in the design of multi-robot and multi-agent systems
that are capable of making intelligent decisions. Such systems range
from software agents to robots that move in unstructured and unknown
environments and to autonomous vehicles that search a city to rescue
people after a disaster.
She is a Fellow of the AAAI and a Distinguished Scientist of the ACM.
She is the chair of the ACM Special Interest Group on Artificial
Intelligence (SIGART), a member of the board of the Autonomous Agents
and Multi-Agent Systems society, and a member of the CRA-W board
co-chairing the Distributed Research Experiences for Undergraduates
(DREU) program.

Speech Title: Why robots are more than just agents

Abstract: Robots are more than just agents because they have a physical body
and interact with the real world through their sensors and actuators.
They also have limited power supply and often limited communications
capabilities. In the talk we will explore how this affects the design
of robot systems and address open challenges in design, validation,
and performance evaluation of robot systems using a variety of examples.

WI 2010 and IAT 2010 will include tutorials providing in-depth background on subjects that are of broad interest to both
the Web intelligence community and the intelligent agent community. The goal of the Tutorial Program is to offer conference
attendees and local participants a stimulating and informative selection of tutorials reflecting current topics in Web
intelligence and intelligent agent. These tutorials will be presented by subject matter experts and will reflect the high
academic and research standards of the WI-IAT 2010 conference. We encourage submissions of proposals on topics that have a
direct relevance to the topics of the conference.

Proposals will be considered for short (2 hrs) and long (half-day) tutorials. A list of recent tutorials collocated with
WI-IATs can be found at WI-IAT 2009 and WI-IAT 2008 websites.

IAT 2010 Industry Track Short Papers

Integration of Multiagent Systems and Service Oriented Architectures in the Steel Industry
Sven Jacobi, Christian Hahn, and David Raber

The 2010 International Conference on Active Media Technology (AMT 2010)
will be held jointly with IEEE/WIC/ACM WI-IAT 2010 at York Univeristy from August 28-30.
Click http://www.yorku.ca/amtbi10/amtbi.php?conf=amt for more information

The 2010 International Conference on Brain Informatics (BI 2010)
will be held jointly with IEEE/WIC/ACM WI-IAT 2010 at York Univeristy from August 28-30
Click http://www.yorku.ca/amtbi10/amtbi.php?conf=bi for more information

WI2010 Final Program Schedule has been released. Please check here for details.

IAT2010 Final Program Schedule has been released. Please check here for details.